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QuantumATK - Atomistic Simulation Feature List

LCAO Density Functional Theory (DFT)

  • Norm-conserving Troullier-Martins pseudopotentials
    • FHI/SG15/PseudoDojo potentials provided for almost all elements of the periodic table, including semi-core potentials for many elements
    • PseudoDojo and SG15 potentials are fully relativistic
  • Around 400 LDA/GGA/MGGA exchange-correlation functionals via libXC
  • Possibility to add custom DFT functionals
  • MetaGGA SCAN functional for significant improvements for energetics over GGA and LDA
  • Methods for accurate band gap calculations of semiconductors and insulators
    • MetaGGA (TB09)
    • DFT+1/2 method (DFT: LDA, GGA, MetaGGA SCAN)
    • Shell DFT-1/2 method enabling scripting of GGA-1/2 parameters
    • Empirical "pseudopotential projector shift" method (parameters provided for Si and Ge)
  • for accurate electronic properties of bulk materials, interfaces and gate stack structures
    • HSE06, B3LYP, B3LYP5, PBE0
    • Dielectric dependent hybrid functional HSE06-DDH, based on using improved material-specific and position-dependent fractions of exact exchange, automatically calculated from density
      • Works for semiconductors, insulators, and metals
    • Large-scale simulations with modest computational resources: LCAO basis sets enable linear scaling with the system size and number of k-points
      • 2-20X speed-up by using Auxiliary Density Matrix Method (ADMM) to obtain large basis set quality results at small basis sets costs
  • Van der Waals models (DFT-D2 and DFT-D3) for LDA, GGA and hybrid DFT functionals
  • Non-collinear, restricted and unrestricted (spin-polarized) calculations
  • Spin-orbit coupling
  • Hubbard U term in both LDA and GGA (also spin-dependent)
    • "Dual", "on-site", and "shell-wise" models
  • Counterpoise correction for basis set superposition errors (BSSE) for bulk, surface and device (NEGF) configurations
  • Ghost atoms (vacuum basis sets) for higher accuracy in the description of surfaces and vacancies
  • Virtual crystal approximation (VCA)
  • Analytical Force and Stress
  • for efficient structural relaxation of large-scale (< 10, 000 atom systems) (preview version)
  • Parallelized via MPI, OpenMP, or OpenMP and MPI together

Plane Wave Density Functional Theory (DFT)

  • Norm-conserving Troullier-Martins pseudopotentials
    • FHI/SG15/PseudoDojo potentials provided for almost all elements of the periodic table, including semi-core potentials for many elements
    • PseudoDojo and SG15 potentials are fully relativistic
  • Projector-augmented wave (PAW) pseudopotentials
    • GPAW data set for LDA/GGA
    • JTH data set for LDA/GGA (includes lanthanides)
  • Around 400 LDA/GGA/MGGA exchange-correlation functionals via libXC
  • Possibility to add custom DFT functionals
  • MetaGGA SCAN functional for significant improvements for energetics over GGA and LDA
  • Methods for accurate band gap calculations of semiconductors and insulators
    • MetaGGA (TB09)
    • Empirical "pseudopotential projector shift" method (parameters provided for Si and Ge)
  • Hybrid functionals for accurate electronic properties of bulk materials, interfaces and gate stack structures
    • HSE06, B3LYP, B3LYP5, PBEO (Implemented using the ACE algorithm)
  • Van der Waals models (DFT-D2 and DFT-D3) for LDA, GGA and hybrid DFT functionals
  • 1D and 3D k·p methods for much faster plane-wave bandstructure, density of states, eigenvalues, and optical spectrum calculations without loss of precision, in particular, with plane-wave HSE
  • Non-collinear, restricted and unrestricted (spin-polarized) calculations
  • Spin-orbit coupling
  • Eigensolvers
    • Generalized Davidson method – stable and robust method
    • for better parallel scaling for large systems (default)
  • Analytical Force and Stress
  • Unique restarting options where plane-wave calculations can be initialized from an LCAO calculation
  • Parallelized via MPI, OpenMP, or OpenMP and MPI together

Semi Empirical Methods

  • Built-in Slater-Koster models for group IV and III-V semiconductors (including strained models)
    • Interface for input of user-defined Slater-Koster parameters
  • Extended Hückel model with over 300 basis sets for (almost) every element in the periodic table
  • Spin polarization term can be added via internal database of spin-split parameters
  • Non-collinear spin
  • Spin-orbit interaction (parameterized)
  • Hartree term for self-consistent response to the electrostatic environment
  • All models adapted for self-consistent calculations through external database of atomic Hartree terms following the DFTB approach
  • Analytical Force and Stress
  • Parallelized via MPI, OpenMP, or OpenMP and MPI together

Force Field Methods

    • Two/three-body potentials: Lennard-Jones (various versions), Coulomb (various versions),
    • Stillinger-Weber, Tersoff (various versions), Brenner, Morse, Buckingham, Vessal, Tosi-Fumi, user-defined tabulated
    • Many-body: EAM, MEAM, Finnis-Sinclair, Sutton-Chen, charge-optimized many-body (COMB)
    • Polarizable: Madden/Tangney-Scandolo, core-shell
    • ReaxFF
    • Valence Force Field (VFF) models
    • Brenner/REBO and Moliere potentials
    • Universal Force Field (UFF) containing parameters for every element in the periodic table
    • Bonded DREIDING, OPLS-AA, OPLS-Min and UFF for polymer, battery electrolyte and organic molecule simulations
      • Automatic potential generation, atom type assignment, and possibility to edit all terms of bonded potentials 
    • Possibility to incorporate partial charges into potentials from different sources, to account for (long-range) electrostatic interactions 
      • These can be calculated to replicate electrostatic interactions from DFT calculations, estimated by QEq or manually assigned 
    • GPU acceleration for organic and oxide potentials (only available in Linux, preview version) 
  • BYOP (Bring Your Own Potential)
    • Python and GUI interface for adding your own or literature potential of any of the supported types
    • GUI to easily set up organic force fields (OPLS, UFF, Dreiding) and combine it with inorganic force fields for surfaces and non-particles.
    • Support for custom combinations of potentials
      • E.g. combine a Stillinger-Weber potential with a Lennard-Jones term to account for van der Waals interaction
      • Several such potentials from literature are already provided: Pedone, Guillot-Sator, Marian-Gastreich, Feuston-Garofalini, Matsui, Leinenweber, and more

Machine-Learned Force Fields

  • Machine-Learned Force Fields,??(), calculate interactions (energy, forces, stress) in an atomic configuration at nearly the same accuracy as ab initio (e.g., DFT), but 1,000-10,000 times more efficient
  • Use Machine-Learned Force Fields (ML-FFs) when no conventional Force Fields exist to describe complex materials accurately and ab initio simulations are too expensive, i.e., for large-scale systems (10,000 – 100,000+ atoms)/long-timescale dynamical simulations:
    • Realistic structure generation of complex multi-element crystalline and amorphous materials, alloys, interfaces, and multilayer stacks
      • Multilayer Builder GUI for building high-k metal gate stacks (HKMGs) 
    • Defect and dopant migration barriers
    • Crystallization and amorphization 
    • Thermal transport 
    • Mechanical properties 
    • Surface processes, such as thermal ALD and ALE
  • With a given parameter set ML FFs can be used for molecular dynamics/time-stamped force-bias Monte Carlo/geometry optimization like any other QuantumATK force field
  • Available pre-trained ML FFs in the QuantumATK library:
    • Bulk crystal and amorphous: Si, SiO2, HfO2, TiN, TiSi, TiNAlO
    • Crystal/amorphous and amorphous/amorphous interfaces: TiN|AlO, Si|SiO2, SiO2|HfO2, HfO2|TiN, Ag|SiO2, Si|Ti|TiSi
    • Surface process simulations: HfCl4 deposition on HfO2 surfaces (ALD)
  • Automated and efficient generation of ML FFs enabling users to develop, systematically improve, and use ML FFs for new materials
    • Framework for automatically generating training configurations, computing training data with DFT, such as energy, forces, stress, fitting to the training data, validating and optimizing hyperparameters
    • Active Learning method to improve initial ML FFs by actively adding training configurations and DFT training data during MD simulations
      • Recommended for amorphous systems, interfaces, systems at high temperatures, surface processes
      • Automatic ML FFs training tools and GUI templates, ensuring minimal amount of training data and time needed, for:
        •  
  • Possibility to combine ML FFs with conventional FFs, DFT and Semi-empirical methods to include additional interactions and improve overall accuracy in specific applications, such as, for example:
    • Long-range D3 dispersion correction: can be important for molecules, molecule-solid interfaces, and solid-liquid interfaces
    • Long-range electrostatic interactions: can help to improve accuracy in the presence of ionic species interacting over large distances beyond the ML FF cutoff
    • Short-range repulsion: can improve the stability in simulations when atoms come too close to each other
  • Supports OpenMP and massively-parallel MPI parallelization

Ion Dynamics for LCAO, PlaneWave, Semi Empirical and ForceField

  • Quasi-Newton LBFGS and FIRE methods for geometry and unit cell optimization (forces and stress)
    • Quick initial optimization using available force fields
    • Simultaneous optimization of forces and stress
    • Optimize structure to specified target stress (hydrostatic or tensor)
    • Pre/post step hooks for custom on-the-fly analysis
    • Constant volume optimization
    • Interrupt a calculation by saving the most recent state
    • Automatic restart
    • Geometry optimization of device structures (also under finite source–drain bias)
  • Computation of dynamical matrix
    • Compute phonon band structure, DOS, and thermal transport
    • Compute and visualize phonon vibration modes
    • Compute the Seebeck coefficient, ZT, and other thermal transport properties by combining ionic and electronic results
    • Zero-point energy and free lattice energy can be obtained from the PhononDensityOfStates
    • Analysis object (vibrational free energy in quasi-harmonic approximation of molecules and bulk)
    •  for speeding up calculations of large systems and improving accuracy
    • Uses crystal symmetries to reduce the number of displacements required
    • for treating electron-phonon coupling effects
      • Based on weighting calculated phonon modes, obtaining displacement vectors of the atomic coordinates and displacing atoms accordingly at various temperatures
  • Calculation of transition states, reaction pathways, and energies
    • Nudged Elastic Bands (NEB) method
    • Support for varying cell shape and size, to simulate e.g. phase changes
    • Climbing image method
    • Parallelized over images
    • Possibility to use pre-defined constraints and set up custom constraints, e.g. external fields
    • Built-in framework to study defect migration paths and energies based on NEB
  • Flexible constraints
    • Fix atoms
    • Separate X, Y, Z constraints
    • Fix center of mass
    • Constrain Bravais lattice type (even when target stress is applied)
    • Fix space group (in geometry optimization)
    • Fix bond length and angles
    • State-of-the-art MD dynamics methods
    • Runs with DFT, semi-empirical models, or classical potentials
    • All thermostats and barostats support linear heating and cooling
    • All barostats support isotropic and anisotropic pressure coupling and linear compression
    • Thermostats and barostats
      • NVE Velocity Verlet
      • NVT Nosé-Hoover with chains
      • NVT/NPT Berendsen
      • NPT Martyna-Tobias-Klein barostat
      • Langevin
    • Several options for initialization of velocities
    • Predefined ForceField-MD and DFT-MD workflow templates
    • Stress-strain MD for simulating the stress response when a system is strained
    • Thermal transport simulations using reverse non-equilibrium MD
    • Predefined or created user-defined pre- and post-step hooks in Python for custom on-the-fly analysis (), custom constraints, , etc.
    • Fine grained control over saving quantities during an MD run at a user defined interval
    • Measured quantities can be plotted along with the MD trajectory animation using a Movie Tool or be used to make custom plots
    • Partial charge analysis
    • Visualization of velocities
    • Interactive analysis tool for trajectory and single configuration properties (also for imported trajectories from LAMMPS, VASP, etc)
      • radial/angular distribution function
      • velocity autocorrelation
      • local mass density profile
      • coordination number profile
      • mean-square displacement
      • nearest neighbor number
      • neutron scattering factor
      • chemical composition profile
      • x-ray scattering
      • velocity/kinetic energy distribution
      • local structure analysis (Voronoi type)
      • temperature profile
      • vibrational density of states
      • specific heat capacity (based on vibrational DOS calculated from MD velocities)
      • infrared spectrum
      • ionic conductivity
      • self-diffusion
      • the above analysis can be performed very efficiently for a selected subset of atoms, also in very large structures
  • Thermo-Mechanical properties
    • Forces and stress (analytic Hellmann–Feynman for DFT)
    • Elastic constants
    • Local stress
    • Glass transition temperature
    • Shear viscosity
  • Global optimization
    • Define custom criteria which can include any combination of material properties
    • Alternative to molecular dynamics for long time-scale equilibration, deposition, amorphization, diffusion, sampling of rare events, etc., either at constant temperature  with a linear heating/cooling ramp or constant pressure
    • Possibility to use hooks for customs on-the-fly analysis or custom constraints
  • Metropolis Monte Carlo Method 
    • Generate realistic fully-coordinated defect-free amorphous/crystalline interface structures using the continuous random network (CRN) method.
    • Long time scale molecular dynamics for finding unknown reaction mechanisms and estimating reaction rates
    • Two options: detailed analysis via phonon partition function, or quick estimate via curvature of NEB path
  • Metadynamics via the
  • Export movies of MD trajectories, phonon vibrations, NEB paths, etc.
    • Monte Carlo builder for polymer melts
      • GUI and Python support for automation
      • Efficiently build high-quality polymer melt or composite structures without long brute-force equilibration MD.
    • Crosslinking reaction tool for which form cross-linked or 3D network structures, as well as rubber-like network structures
    • Homo- and co-polymers, and polymer blends
    • Include additive molecules, surfaces, nanoparticles, or any nanostructure
    • Create your own monomers or use provided monomers from monomer database, add monomers in forward or reverse orientations
    • Automatic assignment of connectivity tags to define monomer linking reactions
    • Automatic potential generation for DREIDING, UFF and OPLS-AA
    • Polymer equilibration methods, such as force-capped-equilibration for initial equilibration, singe-chain mean-field (SCMF) equilibration, energy minimization for relaxing the polymer system, 21 step polymer equilibration automatic workflow
    • Simulation methods, such as MD in the NVE, NVT and NPT ensembles, time-stamped force-biased Monte Carlo, non-equilibrium momentum exchange for modeling heat transfer in polymer systems, and advanced custom techniques via hook functions
    • Support for united atoms and coarse-grained polymers to significantly speed up simulations
    • Analysis tools for plotting end-to-end distances, free-volume, characteristic ratio, molecular order parameters, radius of gyration

Surface Process Simulations

  • Surface process simulation tools to study deposition (ALD), etching (ALE), and sputtering
  • to screen critical reactions in a process, find ideal reactants, optimal reaction conditions for the processes, and
  • Set up and analysis tools to provide atomic-level insight into and to study the impact of incoming kinetic energy, incident angle, the time between impacts, surface temperature, and thermostat layer thickness 
    • Calculate sputtering yield, sticking coefficient, and precursor coverage needed for feature scale and reactor scale models
    •  Use specifically trained Machine-Learned Force Fields (ML FFs) to efficiently simulate thermal ALD and ALE processes with ab initio accuracy
      • Available pre-trained ML FF in the QuantumATK library for HfCl4 deposition on HfO2 surfaces (ALD)
      • Employ a special ML FF training protocol to generate ML FFs for other processes and materials
    • Flexible and intuitive API to set up custom sequences of events or set up more complex workflows
    • Hybrid MD/Force-bias Monte Carlo (FBMC) simulations to increase accessible time-scale and enhance equilibration between two deposition events

Poisson Equation Solvers for LCAO, PlaneWave and Semi Empirical

  • FFT (for periodic systems)
  • Solvers for systems including metallic/dielectric regions:
    • Multigrid
    • Conjugate gradient method (parallelized in memory and execution)
    • “Direct" solver for large-scale calculations (parallelized in memory)
    • Non-uniform grid solver for bulk systems and devices with vacuum/dielectrics regions in one or both transverse directions 
  • FFT2D solver for device configurations that have no metallic and dielectric regions.
  • Metallic gate electrodes and dielectric screening regions
    • Allows for computation of transistor characteristics (gated structures) as well as charge stability diagrams of single-electron transistors
  • Multipole expansion for molecules
  • Dirichlet, von Neumann, or periodic boundary conditions can be specified independently in each direction

Performance Options for LCAO, PlaneWave and Semi Empirical

  • Consistent use of "best in class" standard libraries/algorithms like Intel MKL, ELPA, PETSc, SLEPc, ZMUMPS and FEAST
  • Proprietary sparse matrix library
  • Parallel memory distribution of e.g. the mixing history
  • Automatic adjustment of number of bands above the Fermi level to include
  • Multilevel parallelism
    • Over images in NEB and similarly for other complex tasks
    • Over k-points
    • Over basis functions (using multiple processes per k-point)
    • Also for band structure, DOS etc.
    • Automatic algorithm to determine the default (optimal) number of processes per k-point
  • Caching of data for higher memory usage vs. faster performance - or opposite
  • Use disk space instead of RAM to store grids for Poisson solver
  • for O(N) calculations of very large systems (10,000+ atoms in DFT);
  • Automatic threading intelligence to optimize efficiency when using hybrid MPI/OpenMP parallelization

Electronic Structure Analysis for LCAO, PlaneWave and SemiEmpirical

  • Band structure
    • User defined Brillouin zone path through selection of high symmetry points
    • Fat bandstructure, shows projection onto atoms, spin, orbitals or angular momenta, in any desired combination
    • Effective bandstructure, i.e. unfolding of bandstructure for alloys and other supercells (no constraints on defect location, defect types, element), option to choose projections
    • Local bandstructure
  • Molecular spectrum
    • One-electron spectrum of molecules
    • Projected Gamma-point molecular spectrum for periodic systems
  • Density of states (DOS)
    • Calculated using the tetrahedron method of Gaussian smearing
    • Projection onto atoms, spin, orbitals or angular momenta, in any desired combination
    • Local density of states (can be used to simulate STM images within the Tersoff-Hamann approximation or bulk DOS)
    • Normalize DOS with respect to volume, area, length or a number of atoms in the cell
    • Calculation of carrier concentration from DOS and Fermi distribution
  • Projections of band structure and DOS onto atoms, spin, orbitals or angular momenta, in any desired combination
  • Mulliken populations of atoms, bonds and orbitals 
  • Real-space 3D grid quantities as Python objects allowing for manipulations, evaluation at points,
    • Electron density
    • Partial electron density (simulate STM images within the Tersoff-Hamman approximation)
    • Effective potential
    • Full Hartree or Hartree difference potential
    • Exchange-correlation potential
    • Full electrostatic or electrostatic difference potential
    • Electron localization function (ELF) 
    • Molecular orbitals 
    • Bloch functions, complex wavefunction with phase information 
  • Total/free energy
    • Entropy contribution
  • Polarization and piezoelectric tensor
    • Calculated using the Berry phase approach
    • Optional internal ion relaxation
  • and inverse participation ratio to evaluate localized states
  • Effective mass analysis, including tensor (based on finite difference method or analytic derivative)
  • Bader charges 
  • Born effective charges
  • Fermi surface
    • A framework for studying the properties of a defect in a host material (formation energies, trap levels, migration paths and energies), by setting up and running all the calculations required for a comprehensive study
    • Type of defects: vacancies, substitutionals, interstitials, pairs & larger clusters
    • FNV correction scheme for charged defects with automatic Gaussian model charge fitting
    • Possibility to include vibrational corrections and modify atomic chemical potentials
    • Elastic correction to account for the spurious residual stress caused by a defect centre in a finite supercell of the host material
    • Band gap correction scheme to obtain accurate band gaps for defect trap levels at significantly lower computational cost
    • Possibility to apply constraints and point defect symmetry to reduce computational cost
    • Use friendly script generation for linking simulation outputs to TCAD Sentaurus KMC for further defect characterization

Additional Electronic Structure Analysis for LCAO and Semi Empirical

  • Complex band structure
  • Bulk transmission spectrum
  • module
    • Empirical approach to study various magnetic properties (Heisenberg exchange coupling, exchange stiffness, Curie temperature) at finite temperatures, e.g., to understand phase diagrams, phase transitions, and magnetization dynamics of the magnetic system
  • Spin life time
    • At technologically relevant temperatures (>100 K) the spin life time will be limited by electron-phonon interactions, mediated by spin-orbit coupling (Elliot-Yafet mechanism)
    • Calculate the phonon-limited spin life time from an ElectronPhononCoupling object (if computed with noncollinear spin and spin-orbit coupling)
  • for spin dynamics of magnetic systems (with LCAO)
    • Gilbert damping constant, damping rate, and damping tensor for different life-time broadenings
    • Based on Kamberskys torque-torque correlation model (Lorentzian)
    • Versatile study object for calculating the MAE using the force theorem for and
    • Works with LCAO and PlaneWave calculators
    • Calculate and plot MAE as a function of the chosen coordinate (X/Y/Z) at available theta and phi angles, site/shell/orbital-projected MAE
  • Spin Transfer Torque (STT)
    • Calculate (atom-resolved) STT for MTJs using  (at finite bias) and   (based on zero bias and linear response) (DFT-NEGF based)
  • Orbital moment (with LCAO and spin-orbit coupling)
    • Total orbital moment for each cartesian component together with the norm and atom-resolved moments
    • Can be used to calculate magnetic anisotropy energy
  • Electric field gradients and quadrupole coupling constants (with PlaneWave PAW)
  • Nuclear magnetic resonance (NMR) shielding tensors, isotropic and anisotropic  chemical shielding, chemical shifts
    • Based on GIPAW approach 
    • Works with the PlaneWave PAW calculator

Optical and Electro-Optical Analysis Tools

  • (with LCAO, PlaneWave)
    • Raman tensor, phonon mode intensities and polarization dependent or averaged Raman spectra for incoming light scattered in bulk and 2D materials or nanowires
  • Dielectric properties and infrared spectroscopy () (with LCAO)
    • Static dielectric constant
    • Optical properties, such as refractive indices, extinction coefficients, reflectivity in the THz regime
    • Infrared spectrum
    • Includes both, electronic and ionic contributions, i.e., coupling with vibrations for low frequency
    • Phonon contributions to the results
  • Vibrational spectra for liquids and amorphous materials above their glass transition temperatures can be also obtained from molecular dynamics trajectory
  • (with LCAO)
    • Total, electronic and ionic tensors, and also ionic part for different modes
  • Optical spectrum (with LCAO and PlaneWave)
    • Both contributions, interband and intraband (dominating in metals due to plasmons)
    • Linear electronic susceptibility, refractive indices, absorption from the Kubo-Greenwood formalism (no ionic contribution)
  • Second harmonics generation (SHG) susceptibility (with LCAO and PlaneWave)
    • Spin up/spin down, real, imaginary and absolute values for different tensor components
  • Polar LO-TO phonon splitting of phonon bandstructure

NEGF for LCAO and Semi Empirical

  • Non-equilibrium Green's function (NEGF) method for two-probe systems
    • NEGF description of the electron distribution in the scattering region, with self-energy coupling to two semi-infinite leads (source/drain electrodes)
    • Open boundary conditions (Dirichlet/Dirichlet, Dirichlet/Neumann or  Neumann/Neumann) allows application of finite bias between source and drain for calculation of I-V curve
    • Includes all spill-in contributions for density and matrix elements
    • Use of electronic free energy instead of total energy, as appropriate for open systems
    • Ability to treat two-probe systems with different electrodes (enables studies of single interfaces like metal-semiconductor or p-n junctions, for instance)
    • Ability to add electrostatic gates for transistor characteristics
    • Works with LDA, GGA, MGGA (TB09) and hybrid (HSE06, HSE06-DDH) DFT functionals
  • Surface Green's function method for single surfaces
    • NEGF description of the surface layers, with self-energy coupling to a semi-infinite substrate (replaces the slab approximation with a more physically correct description of surfaces)
    • Appropriate boundary conditions for infinite substrate and infinite vacuum above the surface, both for zero and finite applied bias on the surface
    • Compute surface bandstructure – device density of states evaluated along a k-point route
    • Works with LDA, GGA, MGGA (TB09) and hybrid (HSE06) DFT functionals
  • Performance and stability options
    • Scattering states method for fast contour integration in non-equilibrium (finite bias)
    • O(N) Green’s function calculation and sparse matrix description of central region
    • Double or single semi-circle contour integration for maximum stability at finite bias
    • Ozaki contour integration to capture deep states
    • Sparse self-energy methods to save memory
    • Options to store self-energies to disk, either during calculation (instead of RAM) or permanently, to reuse in other calculations
    • Adaptive (non-regular) k-point integration for transmission coefficients
    • Parallelization:
      • Over left/right electrode self-energies
      • Over contour points (combination of transverse k-points and energy points)
      • Inside the calculation of each contour point
    • Minimal Electrode Concept
      • Reduced electrode - automatically repeated for computing self-energies
      • Works for electrodes that are pure repetitions in the lateral A and B directions and/or in the transport direction C
      • Saves time in the electrode calculation which is O(N3)
  • Calculation of I-V curves
    • Elastic, coherent tunneling transport
      • Combined framework for running multiple source-drain/gate voltage calculations and collecting and analyzing the results
      • “Smart restart“
      • Plot current as function of gate source; current as function of drain-source for one or many gate voltages
      • Show on/off ratio, subthreshold swing, transconductance, DIBL, source-drain saturation voltage
      • Control of gate potential and band alignments
    • Quasi-inelastic and fully inelastic electron-phonon scattering calculations
      • , recommended for molecular contacts or nanostructures (weak electron-phonon coupling)
      • , recommended for bulk-like devices (weak, medium, and strong electron-phonon coupling)
      • Inelastic transmission spectrum (IETS) analysis
    • to efficiently capture the effect of phonon scattering on the I-V curve by creating a canonical average over all phonon modes
  • PhotoCurrent Module
    • Analysis module for calculating the photon-mediated transmission in a device using first-order perturbation theory within the 1st Born approximation
    • Also gives the total current based on illumination by the AM1.5 standard solar spectrum
  • Study Object for Relaxation of Devices
    • Makes use of the  and NEGF to optimize the geometry of a device
    • Possibility to use constraints
  • Analysis of transport mechanisms
    • Transmission coefficients (k-point/energy resolved)
    • Monkhorst-Pack or edge-to-edge zone filling k-point scheme, or sample only part of the Brillouin zone for detailed information
    • Spectral current
    • Transmission spectrum, eigenvalues, and eigenchannels
    • Device density of states, also projected on atoms and angular momenta
    • Voltage drop
    • Molecular projected self-consistent Hamiltonian (MPSH) eigenvalues
    • Current density and transmission pathways
    • Spin-Torque Transfer (STT) for collinear/non-collinear spin
    • Atomic-scale band diagram analysis via LDOS or device DOS
    • Set-up and simulation of GB reflection coefficients for a large set of GBs and GB resistivity as a function of average grain size using Mayadas Shatzkes Model
    • Analysis tools for a large set of different grain boundaries
    • User-friendly script generation for linking simulation outputs to TCAD Raphael FX for interconnect simulations

Special Features for LCAO, PlaneWave, Semi Empirical and NEGF

  • Initialization of a new calculation via the self-consistent density matrix of a converged one (with automatic spin realignment)
  • Initialization of noncollinear spin calculations from collinear or spin-unpolarized ones for improved convergence
  • Custom initial spin-filling schemes
  • Odd/even k-point grids (Monkhorst-Pack or edge-to-edge zone filling), Gamma-centered or with custom shifts
  • Fractional hydrogen pseudopotentials and basis sets (for surface passivation)
  • Low-level interface to extract Green's function, Hamiltonian, overlap matrices, self-energies, etc.
  • for benchmark of pseudopotential/basis set accuracy
  • Flexible and customizable verbosity framework to control the level of output to the log files
  • Region-dependent "c" parameter for TB09 Meta-GGA
  • Occupation functions: FermiDirac, Methfessel-Paxton, Gaussian, ColdSmearing
  • Support for charged systems
  • Simulation of doping and external fields
  • Implicit solvent model

Electron-Phonon Interaction for LCAO and Semi Empirical

  • Extract electron-phonon coupling matrix elements
  • Compute deformation potentials and conductivity/mobility tensors from the Boltzmann equation, with constant, full k-point dependent and/or only energy-dependent relaxation times
  • Compute Seebeck coefficients and thermoelectric ZT (and underlying first moment and thermal conductance tensors)
  • Compute Hall coefficient and Hall conductivity tensors
  • Calculate phonon-limited momentum- and spin lifetimes for different temperatures, broadenings and bands, resolve different phonon modes contributions
  • Automated workflows for dynamical matrix (D) and Hamiltonian derivatives (dH/dR), with a possibility to utilize a Wigner-Seitz scheme for speeding up calculations of large systems and improving accuracy of calculated dynamical matrix
  • k-space symmetries of the Brillouin zone (BZ) can be taken into account for the k-point sampling to significantly reduce computational time
  • Tetrahedron integration method for calculating mobility and resistivity of nontrivial Fermi-surfaces or direct integrations for clever selections of BZ areas
  • Approximate methods for calculating phonon-limited resistivity: constant mean-free path (for nanostructures) and constant relaxation time method (for bulk), postponing the heavy calculation of the full scattering rate or use known rate from experiments
  • Thermal velocity of electrons and holes

Multiscale QuantumATK-Sentaurus Device Workflow for 2D FET Engineering

  • QuantumATK - Sentaurus Device QTX - Sentaurus Device workflow to investigate the impact of various parameters on the 2D material-based FET performance (Id-Vg, Id-Vd, and C-V characteristics)
    • Different 2D materials and number of layers for channel
    • Source/drain materials and orientations
    • Gate stack material parameters
    • Device architecture and dimensions
    • Doping concentrations and interface trap distribution
  • Interactive GUI for setting up and analyzing the workflow results

NanoLab (Graphical User Interface)

  • Atomic geometry builder for molecules, crystals, nanostructures and devices
    • 1st party plugins for setting up interfaces, multilayer stacks, nanowires, nanoparticles, polycrystals, alloys, cleave surfaces, etc.
      • Interface builder
        • Analyze strain for different supercell sizes and crystal rotations
        • Generate good starting interface geometries quickly using classical force fields
        • Optimize interface geometry
      • Multilayer Builder
        • Automatically build nearly defect-free multilayer stacks of amorphous and crystalline layers of desired thicknesses between these materials: Si, SiO2, HfO2, and TiN for high-k metal gate stack (HKMG) applications
        • Pre-trained provided Machine-Learned Force Fields (ML FFs) with MD are automatically used to
          • generate amorphous layers using the melt-quench methodology
          • anneal and optimize/relax each interface
        • In order to build multilayer stacks of other materials and stoichiometries, use Python scripting to add layers and the automatic ML FF training workflow to generate ML FFs for these materials
      • Surface cleaver
        • Select Miller indices, surface Bravais Lattices and cleavage planes
        • Create slabs or supercell geometries
        • Passivation tool for surfaces to remove bonds
      • Grain boundary builder
        • Build grain boundaries based on the coincidence site lattice theory, which is used to match the two grains at the grain boundary
        • Choose between different grain boundary planes and types of grain boundaries (tilt, twist or mixed)
        • Create bulk or device structures
      • Device tool for setting up device structures for transport calculations
        • Add gate electrodes and dielectric screening regions
        • Dope semiconductors
      • Molecular builder
        • Add atoms and build structures through point and click-and-drag interface
        • Supports cut, copy, paste and unlimited undo
        • Edit bond lengths, angles and dihedrals
        • Bonds plug-in for finding, adding or deleting static bonds
        • Perform quick optimization with classical force fields
      • Builder plugin for adsorbing molecules to a surface
        • Define specific sites on the surface where molecules can be attached, at what distance above a surface and orientation
        • Set a number of molecules either by setting a count or the coverage of sites of the selected site type
        • Add different molecule types to the same surface
        • Scripting support to automate adsorption simulations
      • Nanostructures builders
        • Icosahedron builder plugin for building icosahedron nanoparticles
        • Wulff construction tool for building nanoparticles with minimal surface energy
        • Builders for nanostructures like graphene, nanotubes, nanowires, and nanoparticles
      • Polycrystalline builder
      • Builders for amorphous structures
        • Amorphous pre-builder to create a rough initial guess for an amorphous structure
        • Packmol builder plugin for creating amorphous configurations
      • Alloy builders
        • Special Quasi-random Structures (SQS) algorithm for generating random alloys
          • SQS uses a genetic algorithm (unlike other codes that perform an open-ended Monte Carlo simulation, which can be very slow)
          • Supports two-component systems like SixGe1-x or InxGa1-xAs
          • Any type of geometry, also nanowires etc.
        • Generic alloy builder
        • Heusler alloy builder
        • Substitutional alloy builder
    • NEB tools
      • Set up path
      • Edit images collectively or individually
      • Pre-optimize NEB path with Image Dependent Pair Potentials (IDPP)
      • Access interpolation algorithms (LI-LinearInterpolation, HLC-HalgrenLipscomb, and IDDP-ImageDependentPairPotential) in Python scripts for easier automation of NEB path generation
    • Interactive control of structure, select, edit, move (translate, rotate, align), by atom, fragment, etc.
    • Symmetry information tool with the option to symmetrize crystal structures based on approximate space groups
    • Supercells
    • Import/export of most common atomic-scale modeling file formats (extendable by plugins; embedded version of OpenBabel)
    • Pre-defined and custom isotopes
    • Python Console
      • Provides direct Python access to interact with the configurations in the Builder
      • Maps (some) operations in the Builder to Python commands
      • Create pre-defined scripts (”snippets”) to automate repeated tasks
  • Databases
    • Internal structure library with several hundred basic molecules and crystal structures
    • Interface to query online databases such as
    • Support for custom, internal databases based on MongoDB or MySQL
  • Easy setup of calculations, even advanced workflows
    • Full range of functionality for LCAO, PlaneWave, SemiEmpirical and ForceField
    • Framework for setting up and submitting a large number of simulations at once for high-throughput material screening
    • Set up calculations of electronic, optical, thermal, magnetic, mechanical, electron-phonon coupling, piezoelectric, thermoelectric, and other material properties of nanostructures, bulk materials and surfaces
    • Use specialized interface to set up independent tasks for obtaining I-V characteristics, magnetic anisotropy energy, defect formation energies and transition levels
    • Set up molecular dynamics simulations using basic ensembles (NVE, NVT, NPT), more advanced stress-strain, thermal transport techniques or surface process simulations (deposition, etching, sputtering)
    • Use the specialized interface for relaxation of devices and interfaces
    • Edit input files (Python scripts) using the NanoLab built-in editor
    • Customizable script generator
      • Plugin framework for building your own script blocks
      • Save your calculator (LCAO, PlaneWave, SemiEmpirical, ForceField) settings to a preset file, and reuse it in future calculations or ship them to your colleagues
      • Save your workflows including analysis objects as templates and reuse them in future calculations or ship them to your colleagues
  • Editor
    • Search-and-replace
    • Syntax highlighting
    • Python code completion
    • Select font
  • Job Manager
    • Submit and run multiple jobs from the GUI in serial, using threading, and in parallel using MPI, or OpenMP and MPI together
    • Edit job settings on the fly, on (re)submit
    • Advanced machine setup enabling good control of MPIs vs threading and setting maximum number of jobs per queue
    • Submit jobs from the GUI to local machines
    • Submit jobs from the GUI to remote machines
      • A variety of queue types: Torque/PBS, PBSPro, LSF, SLURM, SGE, and direct execution (no queue)
      • Additional queue types can be added by plugins
      • Requires only SSH access from client to server (no server-side daemon is required, all is controlled by the client)
      • Automatically copies input and output files to/from remote resources
      • Built-in SSH key generation and transfer to remote host (no need of 3rd party programs)
      • Diagnostics tool checks that added machine settings are correct
    • Overview currently running tasks for easier control of running jobs
  • Viewer for 3D data
    • High-performance shader-based rendering engine for very large data sets (1M+ atoms and bonds)
    • Isosurfaces, isolines, and contour plots, with graphical repetition and data range control
    • Control atom color, size, transparency, etc.
    • Color atoms by computed quantities, like forces, velocities and by molecules
      • Also works in movies, e.g. MD trajectories
    • Polyhedral rendering of crystals
    • Voxel plot (point cloud) rendering of 3D grids
    • Vector field plots
    • 3D extrusion of contour plans
    • 3D scene camera and lighting control
    • Brillouin zone explorer
    • Export images in most common graphical formats
    • Export (and import) CUBE or simple xyz data files for external plotting
    • Export movies of MD trajectories, phonon vibrations, NEB paths, etc
    • Auto-rotated views can be exported as animated GIFs
    • Interactive 3D measurement tool for distances and angles
  • 2D plot framework
    • Perform advanced editing of plots, such as changing color, line width, etc. of multiple items (several bands for instance) at once, changing title axes, legend, etc., editing grid layout, and adding annotations like arrows and labels
    • Use dual axes: logarithmic and linear scale, and color code the data to match the particular axis
    • Save customized plots for further analysis and reuse plot setups with new data
    • Link and combine plots, e.g. band structure and DOS, for more insightful analysis
    • Fit data to linear and other models, apply smooth rolling or macroscopic averaging transform lines, adjust plot data range for analysis and measure directly in graphs
    • Plot quantities along with the animation using a movie tool
    • Data Plot plugin to easily plot chosen physical quantities and measurements
    • Export plot data to text and import data from a text file to visualize imported data
    • Manipulate plots in scripts,  build your own (), and apply the same plot settings to multiple calculations
  • Project management
      • Organize data files into projects
      • Filter, sort and preview data
      • Perform advanced SQL search queries
      • Overview all data in a project, or focus on particular subsets, then combine data sets from different files for advanced analysis
      • Easily transfer projects between computers, or share with other users
  • Report generator tool high-throughput material screening
    • Extract selected data from multiple calculations and perform analysis by expecting data in a table, grouping results, and visualizing extracted data
    • Create and reuse research protocols, i.e. collection of predefined measurements with visualization, to save time when analyzing data from multiple sets of simulations
    • Save results (in hdf5, csv or excel format) after extracting data
  • GUI interface to external simulation engines
    • Generate input files and plot some of the data obtained with VASP, QuantumESPRESSO, GPAW, Orca, and LAMMPS
    • Import/export structures in external file formats
    • Write addons and plugins in Python using our API to add new functionality to NanoLab

Python Scripting and Automatization

  • QuantumATK is based on Python
    • Python Scripting is the component that binds all the calculators together in a common interface and allows them to synergistically work together
    • All input scripts for setting up simulations use native Python commands together with QuantumATK Python functions
    • Write your own custom scripts in Python or edit the scripts created with the NanoLab GUI Scripter
    • Can run in an interactive mode and in a batch mode
  • QuantumATK Python functions for:
    • Structure generation
      • Define molecule, bulk, surface and device geometries
      • Define Bravais lattices
      • Build special geometries like nanowires, graphene sheets, nanotubes
      • Reproduce workflows from the NanoLab builder using builder Python commands
      • Add new features to the Builder (anything from simple operations to fully interactive widgets)
    • Simulation Setup
      • Define simulation setup for QuantumATK DFT-LCAO, DFT-PlaneWave, Semi-empirical or ForceField
      • Define workflows which combine simulation engines
      • Add post or pre-hooks to Molecular Dynamics simulations, thereby tailoring the MD simulation algorithm
    • Post Analysis
      • Automate analysis and plotting
      • Access internal QuantumATK variables for specialized analyses
      • Add new data analysis capabilities and plot types
      • Batch processing of analyses
      • Combined analysis of different simulations
  • Write addons and plugins in Python, using our API, to add new functionality to NanoLab
    • There are more than 400 QuantumATK classes and functions available to the user, see list
  • Add-on manager for installing plugins written by 草榴社区 QuantumATK team or users
  • Variables are defined with and QuantumATK allows for conversion between different units
  • A variety of Physical Constants available  
  • 3rd party Python modules available from atk python   

 

Platform Support

  •  Self-contained binary installer - no compilation needed, no external library dependencies beyond standard operating system packages
    • Support for all modern 64-bit Windows and Linux versions (detailed system requirements)
    • Provides a complete Python environment with precompiled optimized libraries like numpy/scipy/ScaLAPACK (based on MKL), matplotlib/pylab, MPI4Py, SSL bindings, Qt/PyQt, etc.
  • Parallelization (Windows/Linux)
    • QuantumATK is compiled against Intel MPI and the Intel Math Kernel Library (MKL) which in combination automatically provide an optimized balance between OpenMP threading and MPI
    • Intel MPI is included in the shipment
    • Support for MPICH2/MPICH3 (Ethernet), MVAPICH2 (Infiniband), and other MPICH-compatible libraries
  • Floating license system (SCL from 草榴社区)

Learn more about QuantumATK products

Interested in applying QuantumATK software to your research? Test our software or contact us at quantumatk@synopsys.com to get more information on QuantumATK platform for atomic-scale modeling.